The $fundamentals() method does this and that..
See also
Other InteRactModel methods:
method-add-equation,
method-characteristic-emotion,
method-closest-terms,
method-deflection,
method-max-confirm,
method-modify-identity,
method-optimal-behavior,
method-reidentify
Examples
act <- interact()
#> ✔ dictionary = list(dataset = "usfullsurveyor2015", group = "all")
#> ✔ equations = list(key = "us2010", group = "all")
act$fundamentals("ceo")
#> # Source: ()
#> # A data frame: 1 × 5
#> term component e p a
#> * <chr> <chr> <dbl> <dbl> <dbl>
#> 1 ceo identity 0.71 3.22 1.48
x <- sample(act$dictionary$term, size = 20)
act$fundamentals(x)
#> # Source: ()
#> # A data frame: 22 × 5
#> term component e p a
#> * <chr> <chr> <dbl> <dbl> <dbl>
#> 1 alarm behavior -0.36 1.43 2.22
#> 2 ally identity 2.34 2.15 -0.16
#> 3 constrain behavior -1.91 1.47 0.65
#> 4 contented modifier 2.35 1.7 -0.74
#> 5 convince behavior 1.11 2.14 0.58
#> 6 discomfort behavior -2.29 0.59 0.52
#> 7 displeased modifier -2.07 -0.32 -0.7
#> 8 exalt behavior 0.72 1.08 1.08
#> 9 frustrate behavior -1.87 0.9 1.33
#> 10 greedy modifier -2.45 0.29 1.09
#> # ℹ 12 more rows